Many organizations struggle with managing thousands of services and applications. A typical environment consists of a combination of modern cloud applications, on-premises workloads, and workloads that are in the process of being moved to the cloud. IT and Operations teams can easily be overwhelmed by the large volume of data and activity that is generated across these systems. As a matter of fact, in a recent survey conducted by ESG*, respondents highlighted performance monitoring, lack of skill sets to deploy and manage, and complexity as the top challenges they encounter when it comes to deploying a cloud-based microservices architecture.
To maintain SLAs/SLOs, and resolve issues IT teams depend on metrics, alerts, traces, and logs generated from various siloed tools. This leads to large data volumes and IT alert noise, and delayed incident response. The ideal solution should be able to enforce real-time, closed loop optimization, anchored on a common data platform, with one view across.
Are observability solutions enough to help maintain SLAs and SLOs?
Observability solutions generate large volumes of real-time data and can inundate IT teams and require skilled employees to identify events they can act on. To act on events, observability data needs contextualizing and being able to decipher information from multiple sources such as topology, systems, and historical data. They also focus on natively generated data and may miss context from data that is generated by other sources. Additionally, manually going through these can cause delays in incident resolution.
AIOps aims to resolve some of the challenges faced by observability solutions. While AIOps is very quickly evolving to become a vital part of modern IT management stacks for organizations, the AIOps vendors often struggle with data quality and lack native data collection abilities. They rely on third party sources and observability tools, and this impacts their ability to make meaningful correlations.
Introducing VMware Tanzu Insights
We are excited to announce the availability of VMware Tanzu Insights (formerly VMware Aria Business Insights). Tanzu Insights delivers explainable AI/ML based insights for deeper and contextual troubleshooting for Kubernetes, AWS, and Azure environments on Tanzu Hub. Tanzu Insights enables visibility and correlation of metrics, logs, events, and traces generated from public cloud environments such as AWS, and observability data from VMware Aria Operations for Applications. The solution provides a unified platform enabling customers to leverage visibility and AI/ML based insights holistically.
Notably, proactive insights are automatically delivered to guide the troubleshooting flow and streamline the incident resolution journey. The intelligent grouping of alerts by source brings a cohesive approach to managing multiple alerts effectively. Customers can enjoy benefits such as the ability to:
Gain intelligent observability and actionable insights with rapid identification of impact, causality, and AI-based early warning, offer AI/ML based preventative measures, resulting in reduced mean-time-to-resolution.
Connect relevant data to enable proactive operations and provide a unified experience by bringing together events, traces, metrics, and logs. Unify data from app to infrastructure.
Provide deep issue resolution and analysis for key Kubernetes issues with opinionated and guided workflows
At VMware, we believe we are uniquely positioned to converge AIOps and Observability. Tanzu Insights can leverage the entire VMware ecosystem to take advantage of meaningful data from a variety of sources such as VMware Observability (Aria Operations for Applications), logs, metrics, events, traces, and other sources. Aria Operations for Applications seamlessly integrates with Tanzu Insights, including hundreds of integrations that are part of Aria Operations for Applications.
Key Use Cases
A key advantage of Tanzu Insights is the ability to present events in real-time sequence, eliminating the need for juggling multiple isolated tools. By leveraging a unified data platform, Tanzu Hub, users gain access to a single source of truth, ensuring faster and more effective issue resolution and remediation. This consolidated approach boosts operational efficiency, simplifies decision-making, and ultimately enhances the overall reliability of your systems.
Holistic Impact View – Tanzu Insights can help visualize the Impact on your applications, using alerts from multiple sources, it provides a holistic view of the application environment – including impact scale and overall impact to platform and underlying infrastructure.
Figure 1. Holistic Impact View.
Detailed Observations – Observations are based on multiple sources to help identify issues across different stacks based on observations to better understand the problem progression and scale. For example, issues might lie within different services in the Kubernetes cluster and Tanzu Insights can help pinpoint the issue by correlating information from various sources.
Figure 2. Observations based on multiple sources.
Fast Issue Resolution – Achieve fast troubleshooting of your infrastructure, applications and Kubernetes environments using correlated events, overall topology views, and a timeline view that showcases a detailed timeline of events across your environments and reduce MTTR (mean-time-to-resolve) and maintain SLOs.
